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INTRODUCTION
Documenting safe and adequate drinking water quality at the consumers' taps requires frequent and regular monitoring of the water quality in water distribution networks (WDNs) (European Parliament & Council 1998). However, principles for where to collect the samples are not specified. Since it is practically impossible to check the water quality at every node in the pipe system, it is important to optimize the monitoring strategy to achieve the best possible coverage with as low number of samples as possible.
The increasing size and complexity of urban WDNs also increases the difficulties of assessing water movement patterns in the system. Therefore, network segmentation has become a main field of research (e.g. Giustolisi & Ridolfi 2014; Perelman et al. 2015). The design of district metered areas, where incoming and outgoing quantities of water are metered, has been introduced to improve leakage control (e.g. Morrison et al. 2007) or security during contamination events (Grayman et al. 2009). Usually, district metered areas are in the size of 1,000-5,000 connections (Grayman et al. 2009) and in the case of large networks it can be difficult to analyze patterns in water movement. Therefore, Deuerlein (2008) and Perelman & Ostfeld (2011) developed network simplification tools based on graph theory, which can provide deeper knowledge of the water movement inside complex WDNs. Moreover, network decomposition of large WDNs can be used for contaminant source identification in combination with application of source identification algorithms (Deuerlein et al. 2014). Such backtracking methodologies can be developed to find the most likely set of contaminating nodes based on reverse hydraulics and water quality sensor alarms (e.g. Salomons & Ostfeld 2010). Even though the execution time of such algorithms may be low, the approach is still challenged when an emergency response is needed in WDNs with random sampling locations and only a few sensor results are available.
In case of an emergency with an unknown contamination source, models and algorithms have to be modified and the utilities may waste valuable time. Thus, tools are needed to support immediate response plans for utilities. These can be prepared beforehand and are ready to use, independent of where the contamination has been detected.
WDNs can be simplified through a topological analysis by dividing the WDN into ‘strongly connected clusters’...